Pricing and Returns Under Reversed Information Asymmetry
Abstract
This project extends a game-theoretic model of monopoly pricing and return policy under three information structures: an uninformed firm, an equally informed firm that observes consumer type, and a firm that observes consumer type and a consumer's own realized product valuation before they do themselves, a "reversed information asymmetry" typical of platforms with rich behavioural data. Building on the base model's closed-form profit results, we derive sales, return rates, refund outlays, and total revenue in full, not just profit, for every equilibrium across all three regimes, under both costless returns and a realistic extension with consumer hassle costs and partial refunds. This reveals structure the profit formulas alone conceal: an uninformed firm's revenue and refund costs, unlike its sales and profit, do not scale by any fixed ratio once hassle costs are introduced, since personalized pricing under partial refunds embeds a logarithmic term the frictionless case lacks. We also identify a genuine discontinuity: as the hassle cost shrinks toward zero, the uninformed firm's optimal sales, returns, and profit converge not to its own frictionless benchmark, but to the equally informed firm's values, since even infinitesimal friction unlocks price-based screening that a costless return forecloses entirely. The project's central result is that a rational buyer who observes any off-path price different from the firm's honest, optimal pricing should conclude that their own true valuation is low, and refuse to buy. We prove this formally using the D1 equilibrium refinement (Cho and Kreps, 1987) applied to the fully informed firm's return-inducing signalling game, showing that truthful price and refund signalling is the unique equilibrium that survives any reasonable off-path belief. Extending this to partial refunds shows credibility further requires the refund itself to clear an explicit dollar threshold, not merely that a return policy exists. Supervisors: Professor Murray Lei and Professor Anton Ovchinnikov